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file:Figure-3.jpg|{{figure number|3}}A shale sample imaged using SE1 signal (left) and SE2 signal (right). Surface-specific information such as pore space and surface roughness is evident in the SE1 image. The SE2 image has more compositional influence, displaying organic matter (OM) bodies that are not evident in the SE1 image.<ref name=Huangetal_2013 />

file:Figure-3.jpg|{{figure number|3}}A shale sample imaged using SE1 signal (left) and SE2 signal (right). Surface-specific information such as pore space and surface roughness is evident in the SE1 image. The SE2 image has more compositional influence, displaying organic matter (OM) bodies that are not evident in the SE1 image.<ref name=Huangetal_2013 />

file:M102Ch1Fg4.jpg|{{figure number|4}}SE2 (a) and BSE1 (b) image of a cross section of a shale rock. Note that the contrast between carbonate (Ca) and silica (SiO₂) grains is much higher in BSE1; the topographical information is greater in the SE2 image (OM-associated nanopores are not visible in BSE1).<ref name=Huangetal_2013 />

file:M102Ch1Fg4.jpg|{{figure number|4}}SE2 (a) and BSE1 (b) image of a cross section of a shale rock. Note that the contrast between carbonate (ca) and silica (si) grains is much higher in BSE1; the topographical information is greater in the SE2 image (OM-associated nanopores are not visible in BSE1).<ref name=Huangetal_2013 />

file:M102Ch1Fg5.jpg|{{figure number|5}}A BSE2 image of gold (Au) nanoparticles showing crystallographic contrast.<ref name=Huangetal_2013 />]]

file:M102Ch1Fg5.jpg|{{figure number|5}}A BSE2 image of gold (Au) nanoparticles showing crystallographic contrast.<ref name=Huangetal_2013 />

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effects of higher landing energy and deeper specimen interaction, including more compositional and less topographical information.

effects of higher landing energy and deeper specimen interaction, including more compositional and less topographical information.

[[:file:M102Ch1Fg4.jpg|Figure 4]]a shows an SE2 image of a cross section of a shale sample that has been polished by argon-ion milling, a sample preparation technique that consists of using one or more beams of argon ions to gently polish the surface of a sample by sputtering away material, thus providing an extremely smooth surface for SEM investigation. The image was acquired with an Everhart-Thornley type secondary electron detector.

[[:file:M102Ch1Fg4.jpg|Figure 4]]a shows an SE2 image of a [[cross section]] of a shale sample that has been polished by argon-ion milling, a sample preparation technique that consists of using one or more beams of argon ions to gently polish the surface of a sample by sputtering away material, thus providing an extremely smooth surface for SEM investigation. The image was acquired with an Everhart-Thornley type secondary electron detector.

The SE2 image contrast reveals both topographical and compositional information due to the greater sample interaction depth of SE2 electrons. High SE yield is scaled as lighter shades of gray, and low SE yield is scaled as dark shades of gray in SEM images. Pores and fractures appear dark in the SE2 image, reflecting lower secondary electron yield from negative depressions than from elsewhere on the sample surface. Therefore, porosity information can be readily characterized with the SE2 electrons.

The SE2 image contrast reveals both topographical and compositional information due to the greater sample interaction depth of SE2 electrons. High SE yield is scaled as lighter shades of gray, and low SE yield is scaled as dark shades of gray in SEM images. Pores and [[fracture]]s appear dark in the SE2 image, reflecting lower secondary electron yield from negative depressions than from elsewhere on the sample surface. Therefore, [[porosity]] information can be readily characterized with the SE2 electrons.

The same cross section was imaged with BSE1 with the Energy-selective backscatter (EsB) detector (Figure 4b). The image contrast (grayscale variation) reflects compositional variations (mean atomic number) of the sample. For example, the midgray represents silica matrix; the darker level represents organic matter. The brighter gray level reflects higher density carbonate phases, and the brightest gray level represents pyrite. Note the greater compositional contrast provided by the BS1 image (Figure 4b) over the SE2 image (Figure 4a). Although SE2 and BS1 images are capable of providing compositional information, auxiliary techniques, such as energy-dispersive x-ray spectrometry (EDS), are required to characterize elemental composition.

The same cross section was imaged with BSE1 with the energy-selective backscatter (EsB) detector (Figure 4b). The image contrast (grayscale variation) reflects compositional variations (mean atomic number) of the sample. For example, the midgray represents [[silica]] matrix; the darker level represents organic matter. The brighter gray level reflects higher density [[carbonate]] phases, and the brightest gray level represents [[pyrite]]. Note the greater compositional contrast provided by the BS1 image (Figure 4b) over the SE2 image (Figure 4a). Although SE2 and BS1 images are capable of providing compositional information, auxiliary techniques, such as energy-dispersive x-ray spectrometry (EDS), are required to characterize elemental composition.

Compared to BSE1, for which the contrast is modulated by mean atomic number differences, BSE2 yield depends strongly on crystalline structures such as grain orientations. [[:file:M102Ch1Fg5.jpg|Figure 5]] shows a BSE2 image of gold (Au) nanoparticles. Contrast corresponding to different grains is revealed in the image despite all the chemically identical grains. Therefore, BSE2 electrons can be used to image crystallographic contrast in polycrystalline materials.

Compared to BSE1, for which the contrast is modulated by mean atomic number differences, BSE2 yield depends strongly on crystalline structures such as grain orientations. [[:file:M102Ch1Fg5.jpg|Figure 5]] shows a BSE2 image of [[gold]] (Au) nanoparticles. Contrast corresponding to different grains is revealed in the image despite all the chemically identical grains. Therefore, BSE2 electrons can be used to image crystallographic contrast in polycrystalline materials.

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file:M102Ch1Fg6.jpg|{{figure number|6}}(a) A BSE and CL image of a polished shale sample. Orange-hued quartz grains reflect low-grade metamorphic origin (slate); blue-hued quartz grains indicate higher grade metamorphism (phyllite-schist). (b) Detail of a large quartz grain in center of image (arrow) displays multiple generations of growth in CL; this distinction in zoning is not visible in SEM.<ref name=Huangetal_2013 />

file:M102Ch1Fg6.jpg|{{figure number|6}}(a) A BSE and CL image of a polished shale sample. Orange-hued [[quartz]] grains reflect low-grade metamorphic origin (slate); blue-hued quartz grains indicate higher grade metamorphism (phyllite-schist). (b) Detail of a large quartz grain in center of image (arrow) displays multiple generations of growth in CL; this distinction in zoning is not visible in SEM.<ref name=Huangetal_2013 />

file:M102Ch1Fg7.jpg|{{figure number|7}}An example of an x-ray spectrum acquired from a shale sample. Individual peaks indicate an elevated concentration of a given element. C=carbon, O=oxygen, Mg=magnesium, Al=aluminum, Si=silicon, Ca=calcium.<ref name=Huangetal_2013 />

file:M102Ch1Fg7.jpg|{{figure number|7}}An example of an x-ray spectrum acquired from a shale sample. Individual peaks indicate an elevated concentration of a given element. C=carbon, O=oxygen, Mg=magnesium, Al=aluminum, Si=silicon, Ca=calcium.<ref name=Huangetal_2013 />

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Another complimentary technique is the detection of CL, in which certain materials will emit photons in the form of visible light as a result of interactions between specimen electrons and primary beam electrons. [[:file:M102Ch1Fg6.jpg|Figure 6]] shows an example of the effects of CL on a shale sample. The image was acquired with a dedicated CL detector. Variations in CL emission caused by mineral impurities could indicate provenance of individual quartz grains. Cathodoluminescence can also be used to differentiate between generations of quartz growth that are not distinguishable in SEM due to identical mean atomic number.

Another complimentary technique is the detection of CL, in which certain materials will emit photons in the form of visible light as a result of interactions between specimen electrons and primary beam electrons. [[:file:M102Ch1Fg6.jpg|Figure 6]] shows an example of the effects of CL on a shale sample. The image was acquired with a dedicated CL detector. Variations in CL emission caused by mineral impurities could indicate provenance of individual [[quartz]] grains. Cathodoluminescence can also be used to differentiate between generations of quartz growth that are not distinguishable in SEM due to identical mean atomic number.

==X-ray microanalysis==

==X-ray microanalysis==

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file:Figure-8.jpg|{{figure number|8}}A secondary electron image of a shale sample with an EDS-derived mineral segmentation overlay. In the segmented region, blue = carbonate, green = clay minerals, yellow = quartz, pink = feldspar, white = pyrite, and gray = organic matter.<ref name=Huangetal_2013 />

file:Figure-8.jpg|{{figure number|8}}A secondary electron image of a shale sample with an EDS-derived mineral segmentation overlay. In the segmented region, blue = carbonate, green = clay minerals, yellow = [[quartz]], pink = feldspar, white = pyrite, and gray = organic matter.<ref name=Huangetal_2013 />

file:Figure-9.jpg|{{figure number|9}}At left, a schematic diagram of operation of an FIB-SEM system. The FIB sputters away a thin layer of the sample at a time, while the electron beam/detector system captures an image of each newly exposed surface. At right, a picture of a commercial FIB-SEM CrossBeam™ system, Auriga.<ref name=Huangetal_2013 />

file:Figure-9.jpg|{{figure number|9}}At left, a schematic diagram of operation of an FIB-SEM system. The FIB sputters away a thin layer of the sample at a time, while the electron beam/detector system captures an image of each newly exposed surface. At right, a picture of a commercial FIB-SEM CrossBeam™ system, Auriga.<ref name=Huangetal_2013 />

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==Focused ion beam applications==

==Focused ion beam applications==

Focused ion beam (FIB) systems also find a growing number of applications in geology.<ref name=Goldsteinetal_2003 /> In a typical FIB-SEM system, an extraction field is applied to a gallium (Ga) liquid metal ion source to field emit Ga ions and form a Ga beam. Due to the higher atomic mass, the Ga beam not only can be used to generate electron and ion images, but also may be used to mill samples to remove material. [[:file:Figure-9.jpg|Figure 9a]] shows the schematic diagram of an FIB-SEM system where a cross section of the sample is milled by a Ga FIB beam and is imaged simultaneously by the SEM. This milling and imaging process can be automated in a serial fashion to acquire a stack of two-dimensional images, from which a 3-D image volume can be constructed from the data set. This technique is particularly useful in revealing the 3-D distribution of mineral types, organic matter, porosity, and the like in shale (and other rock) samples.

Focused ion beam (FIB) systems also find a growing number of applications in geology.<ref name=Goldsteinetal_2003 /> In a typical FIB-SEM system, an extraction field is applied to a gallium (Ga) liquid metal ion source to field emit Ga ions and form a Ga beam. Due to the higher atomic mass, the Ga beam not only can be used to generate electron and ion images, but also may be used to mill samples to remove material. [[:file:Figure-9.jpg|Figure 9a]] shows the schematic diagram of an FIB-SEM system where a [[cross section]] of the sample is milled by a Ga FIB beam and is imaged simultaneously by the SEM. This milling and imaging process can be automated in a serial fashion to acquire a stack of two-dimensional images, from which a 3-D image volume can be constructed from the data set. This technique is particularly useful in revealing the 3-D distribution of mineral types, organic matter, porosity, and the like in shale (and other rock) samples.

Scanning electron microscopy provides different modes and techniques for acquiring high-quality images of shale and other rock samples. The images in this chapter demonstrate their fine resolution and their applicability for the characterization of shale reservoirs.

Scanning electron microscopy provides different modes and techniques for acquiring high-quality images of shale and other rock samples. The images in this chapter demonstrate their fine resolution and their applicability for the characterization of shale reservoirs.